Prediction of genomic breeding values for reproductive traits in Nellore heifers
The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle. A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-pheno...
Gespeichert in:
| Veröffentlicht in: | Theriogenology 2019-02, Vol.125, p.12-17 |
|---|---|
| Hauptverfasser: | , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 17 |
|---|---|
| container_issue | |
| container_start_page | 12 |
| container_title | Theriogenology |
| container_volume | 125 |
| creator | Costa, Raphael Bermal Irano, Natalia Diaz, Iara Del Pilar Solar Takada, Luciana Hermisdorff, Isis da Costa Carvalheiro, Roberto Baldi, Fernando de Oliveira, Henrique Nunes Tonhati, Humberto de Albuquerque, Lucia Galvão |
| description | The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle.
A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits. |
| doi_str_mv | 10.1016/j.theriogenology.2018.10.014 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2126911450</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0093691X18309683</els_id><sourcerecordid>2126911450</sourcerecordid><originalsourceid>FETCH-LOGICAL-c386t-3768afcaea221605b0af258d7f40c067afd519fe3b8f19d2a6e713c5420f3e083</originalsourceid><addsrcrecordid>eNqNkE1LBDEMhosoun78BenBg5dZk3anMwNeRPwCUQ8K3kq3k65dZqfazi747-2yKnjzlJC8Sd48jJ0gjBFQnc3HwxtFH2bUhy7MPscCsM6tMeBki42wrppCConbbATQyEI1-LrH9lOaA4BUCnfZnsxJjaIasaenSK23gw89D46vly685dNIudzP-Mp0S0rchcgjvcfQLrN2RXyIxg-J-54_UNeFSPyNvKOYDtmOM12io-94wF6ur54vb4v7x5u7y4v7wspaDYWsVG2cNWSEQAXlFIwTZd1WbgIWVGVcW2LjSE5rh00rjKIKpS0nApwkqOUBO93szaY-ssVBL3yy2YvpKSyTFijy5zgpIUvPN1IbQ0qRnH6PfmHip0bQa6Z6rv8y1Wum625mmsePvy8tpwtqf4d_IGbB9UZA-d-Vp6iT9dTbTDCSHXQb_P8ufQHCR5Iz</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2126911450</pqid></control><display><type>article</type><title>Prediction of genomic breeding values for reproductive traits in Nellore heifers</title><source>ScienceDirect Journals (5 years ago - present)</source><creator>Costa, Raphael Bermal ; Irano, Natalia ; Diaz, Iara Del Pilar Solar ; Takada, Luciana ; Hermisdorff, Isis da Costa ; Carvalheiro, Roberto ; Baldi, Fernando ; de Oliveira, Henrique Nunes ; Tonhati, Humberto ; de Albuquerque, Lucia Galvão</creator><creatorcontrib>Costa, Raphael Bermal ; Irano, Natalia ; Diaz, Iara Del Pilar Solar ; Takada, Luciana ; Hermisdorff, Isis da Costa ; Carvalheiro, Roberto ; Baldi, Fernando ; de Oliveira, Henrique Nunes ; Tonhati, Humberto ; de Albuquerque, Lucia Galvão</creatorcontrib><description>The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle.
A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits.</description><identifier>ISSN: 0093-691X</identifier><identifier>EISSN: 1879-3231</identifier><identifier>DOI: 10.1016/j.theriogenology.2018.10.014</identifier><identifier>PMID: 30368127</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Genomic selection ; Predicative ability ; Reproductive efficiency ; SNP</subject><ispartof>Theriogenology, 2019-02, Vol.125, p.12-17</ispartof><rights>2018 Elsevier Inc.</rights><rights>Copyright © 2018. Published by Elsevier Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-3768afcaea221605b0af258d7f40c067afd519fe3b8f19d2a6e713c5420f3e083</citedby><cites>FETCH-LOGICAL-c386t-3768afcaea221605b0af258d7f40c067afd519fe3b8f19d2a6e713c5420f3e083</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0093691X18309683$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30368127$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Costa, Raphael Bermal</creatorcontrib><creatorcontrib>Irano, Natalia</creatorcontrib><creatorcontrib>Diaz, Iara Del Pilar Solar</creatorcontrib><creatorcontrib>Takada, Luciana</creatorcontrib><creatorcontrib>Hermisdorff, Isis da Costa</creatorcontrib><creatorcontrib>Carvalheiro, Roberto</creatorcontrib><creatorcontrib>Baldi, Fernando</creatorcontrib><creatorcontrib>de Oliveira, Henrique Nunes</creatorcontrib><creatorcontrib>Tonhati, Humberto</creatorcontrib><creatorcontrib>de Albuquerque, Lucia Galvão</creatorcontrib><title>Prediction of genomic breeding values for reproductive traits in Nellore heifers</title><title>Theriogenology</title><addtitle>Theriogenology</addtitle><description>The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle.
A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits.</description><subject>Genomic selection</subject><subject>Predicative ability</subject><subject>Reproductive efficiency</subject><subject>SNP</subject><issn>0093-691X</issn><issn>1879-3231</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqNkE1LBDEMhosoun78BenBg5dZk3anMwNeRPwCUQ8K3kq3k65dZqfazi747-2yKnjzlJC8Sd48jJ0gjBFQnc3HwxtFH2bUhy7MPscCsM6tMeBki42wrppCConbbATQyEI1-LrH9lOaA4BUCnfZnsxJjaIasaenSK23gw89D46vly685dNIudzP-Mp0S0rchcgjvcfQLrN2RXyIxg-J-54_UNeFSPyNvKOYDtmOM12io-94wF6ur54vb4v7x5u7y4v7wspaDYWsVG2cNWSEQAXlFIwTZd1WbgIWVGVcW2LjSE5rh00rjKIKpS0nApwkqOUBO93szaY-ssVBL3yy2YvpKSyTFijy5zgpIUvPN1IbQ0qRnH6PfmHip0bQa6Z6rv8y1Wum625mmsePvy8tpwtqf4d_IGbB9UZA-d-Vp6iT9dTbTDCSHXQb_P8ufQHCR5Iz</recordid><startdate>20190201</startdate><enddate>20190201</enddate><creator>Costa, Raphael Bermal</creator><creator>Irano, Natalia</creator><creator>Diaz, Iara Del Pilar Solar</creator><creator>Takada, Luciana</creator><creator>Hermisdorff, Isis da Costa</creator><creator>Carvalheiro, Roberto</creator><creator>Baldi, Fernando</creator><creator>de Oliveira, Henrique Nunes</creator><creator>Tonhati, Humberto</creator><creator>de Albuquerque, Lucia Galvão</creator><general>Elsevier Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20190201</creationdate><title>Prediction of genomic breeding values for reproductive traits in Nellore heifers</title><author>Costa, Raphael Bermal ; Irano, Natalia ; Diaz, Iara Del Pilar Solar ; Takada, Luciana ; Hermisdorff, Isis da Costa ; Carvalheiro, Roberto ; Baldi, Fernando ; de Oliveira, Henrique Nunes ; Tonhati, Humberto ; de Albuquerque, Lucia Galvão</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-3768afcaea221605b0af258d7f40c067afd519fe3b8f19d2a6e713c5420f3e083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Genomic selection</topic><topic>Predicative ability</topic><topic>Reproductive efficiency</topic><topic>SNP</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Costa, Raphael Bermal</creatorcontrib><creatorcontrib>Irano, Natalia</creatorcontrib><creatorcontrib>Diaz, Iara Del Pilar Solar</creatorcontrib><creatorcontrib>Takada, Luciana</creatorcontrib><creatorcontrib>Hermisdorff, Isis da Costa</creatorcontrib><creatorcontrib>Carvalheiro, Roberto</creatorcontrib><creatorcontrib>Baldi, Fernando</creatorcontrib><creatorcontrib>de Oliveira, Henrique Nunes</creatorcontrib><creatorcontrib>Tonhati, Humberto</creatorcontrib><creatorcontrib>de Albuquerque, Lucia Galvão</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Theriogenology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Costa, Raphael Bermal</au><au>Irano, Natalia</au><au>Diaz, Iara Del Pilar Solar</au><au>Takada, Luciana</au><au>Hermisdorff, Isis da Costa</au><au>Carvalheiro, Roberto</au><au>Baldi, Fernando</au><au>de Oliveira, Henrique Nunes</au><au>Tonhati, Humberto</au><au>de Albuquerque, Lucia Galvão</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of genomic breeding values for reproductive traits in Nellore heifers</atitle><jtitle>Theriogenology</jtitle><addtitle>Theriogenology</addtitle><date>2019-02-01</date><risdate>2019</risdate><volume>125</volume><spage>12</spage><epage>17</epage><pages>12-17</pages><issn>0093-691X</issn><eissn>1879-3231</eissn><abstract>The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle.
A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>30368127</pmid><doi>10.1016/j.theriogenology.2018.10.014</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0093-691X |
| ispartof | Theriogenology, 2019-02, Vol.125, p.12-17 |
| issn | 0093-691X 1879-3231 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2126911450 |
| source | ScienceDirect Journals (5 years ago - present) |
| subjects | Genomic selection Predicative ability Reproductive efficiency SNP |
| title | Prediction of genomic breeding values for reproductive traits in Nellore heifers |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T17%3A52%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prediction%20of%20genomic%20breeding%20values%20for%20reproductive%20traits%20in%20Nellore%20heifers&rft.jtitle=Theriogenology&rft.au=Costa,%20Raphael%20Bermal&rft.date=2019-02-01&rft.volume=125&rft.spage=12&rft.epage=17&rft.pages=12-17&rft.issn=0093-691X&rft.eissn=1879-3231&rft_id=info:doi/10.1016/j.theriogenology.2018.10.014&rft_dat=%3Cproquest_cross%3E2126911450%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2126911450&rft_id=info:pmid/30368127&rft_els_id=S0093691X18309683&rfr_iscdi=true |